Papers › Cross-lingual Lexical Sememe Prediction

Cross-lingual Lexical Sememe Prediction

1 Oct 2018EMNLP 2018 10archive 2025-07-28

Fanchao Qi, Yankai Lin, Maosong Sun, Hao Zhu, Ruobing Xie, Zhiyuan Liu

Sememes are defined as the minimum semantic units of human languages. As important knowledge sources, sememe-based linguistic knowledge bases have been widely used in many NLP tasks. However, most languages still do not have sememe-based linguistic knowledge bases. Thus we present a task of cross-lingual lexical sememe prediction, aiming to automatically predict sememes for words in other languages. We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction. Experimental results on real-world datasets show that our proposed model achieves consistent and significant improvements as compared to baseline methods in cross-lingual sememe prediction. The codes and data of this paper are available at \url{https://github.com/thunlp/CL-SP}.

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Learning Word EmbeddingsMultilingual Word EmbeddingsPredictionWord Embeddings

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